Table REF  presents the actual training times measured for a global model (MultVAE [1]}) and LOCA for several benchmark datasets. First, the time taken to train a single local model is approximately 2–6 times less than that for MultVAE [1]}. We also observe that the training time for 1, 2, and 5 local models is not significantly different, as we utilize 8x-parallelism with a multi-core. For 10 or more local models, the training time increases linearly; the increase in training time within the effective parallelism from 1 to 5 is mainly due to the variance in the size of the local model. The datasets with higher concentration shown in Table REF , e.g., MovieLens, tend to have higher variance in the size of the local model, leading to a longer waiting time for the largest local model.
